class_docstr: Saves the Euclidean distance of linked nodes in its edge attributes
  (functional name: :obj:`distance`). Each distance gets globally normalized
  to a specified interval (:math:`[0, 1]` by default).
  
  Args:
      norm (bool, optional): If set to :obj:`False`, the output will not be
          normalized. (default: :obj:`True`)
      max_value (float, optional): If set and :obj:`norm=True`, normalization
          will be performed based on this value instead of the maximum value
          found in the data. (default: :obj:`None`)
      cat (bool, optional): If set to :obj:`False`, all existing edge
          attributes will be replaced. (default: :obj:`True`)
      interval ((float, float), optional): A tuple specifying the lower and
          upper bound for normalization. (default: :obj:`(0.0, 1.0)`)
code: def __repr__(self) -> str:
      return (
          f"{self.__class__.__name__}(norm={self.norm}, "
          f"max_value={self.max})"
      )
  
file_path: pytorch_geometric/torch_geometric/transforms/distance.py
imports: from typing import Optional, Tuple
  import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
label_desc: Use image node_id 3 for calling the Distance obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str